Endogenous dynamics of innovation networks in the German automotive industry: analysing structural network evolution using a stochastic actor-oriented approach

Daniel Hain, Tobias Buchmann, Muhamed Kudic and Matthias Müller
Authors registered in the RePEc Author Service: Matthias Mueller

International Journal of Computational Economics and Econometrics, 2018, vol. 8, issue 3/4, 325-344

Abstract: The generation of innovation is well known to be a social process depending on mutual interactions, aiming at accessing and exchanging knowledge in order to generate novel goods and services. Accordingly, interest in interfirm innovation networks has increased sharply over the last decade. Preceding research indicates that the structural dynamics of networks is driven both by endogenous and exogenous forces. In particular, we focus on the role of the endogenous determinants of the network evolution of interfirm networks - a category of often underestimated forces. We employ a longitudinal dataset that comprises German automotive firms' performance between 2002 and 2006 and apply a stochastic actor-oriented model (SAOM) designed to analyse both the endogenous and exogenous determinants of network change. Our results show that endogenous determinants - approximated by measures for local and global clustering - exhibit greater explanatory power than exogenous firm characteristics such as age, size, and R%D activity.

Keywords: network evolution; network endogeneity; innovation networks; automotive industry; stochastic actor-oriented approach. (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijcome:v:8:y:2018:i:3/4:p:325-344

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